Mobile device attention detection

ABSTRACT

Methods, apparatus, systems and articles of manufacture are disclosed for mobile device attention detection. An example apparatus includes a mobile meter to receive, from an external device, a signal to gather user attention data, and transmit the user attention data. The example apparatus further includes an interval timer to activate a time period for determining attention of a user. The example apparatus further includes an attention determiner to generate the user attention data during the time period.

FIELD OF THE DISCLOSURE

This disclosure relates generally to audience measurement and, moreparticularly, to mobile device attention detection.

BACKGROUND

Audience viewership data is collected and used by audience measuremententities (AMEs) to determine exposure statistics (e.g., viewershipstatistics) for different media. Some audience viewership data may becollected through device meters that detect media watermarks or mediasignatures associated with media presented via media presentationdevices. Information from the device meters are processed by the AME todetermine useful media exposure data and associated statistics.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example environment in which mobile deviceattention is detected in accordance with the teachings of thisdisclosure.

FIG. 2 is a block diagram representative of the example attentiondeterminer of FIG. 1 .

FIG. 3 is a flowchart representative of machine readable instructionswhich may be executed to implement an example set meter included in theset device of FIG. 1 .

FIG. 4 is a flowchart representative of machine readable instructionswhich may be executed to implement the example mobile device of FIG. 1 .

FIG. 5 is a flowchart representative of machine readable instructionswhich may be executed to implement an example attention determinerincluded in the mobile device of FIG. 1 .

FIG. 6 is a flowchart representative of machine readable instructionswhich may be executed to implement an example camera controller andcamera data generator included in the attention determiner of FIG. 2 .

FIG. 7 is a flowchart representative of machine readable instructionswhich may be executed to implement an example interaction determinerincluded in the attention determiner of FIG. 2 .

FIG. 8 is a block diagram of an example processing platform structuredto execute the instructions of FIG. 3 to implement the example setdevice of FIG. 1 .

FIG. 9 is a block diagram of an example processing platform structuredto execute the instructions of FIGS. 4, 5, 6, and 7 to implement theexample mobile device of FIG. 1 .

The figures are not to scale. In general, the same reference numberswill be used throughout the drawing(s) and accompanying writtendescription to refer to the same or like parts.

Descriptors “first,” “second,” “third,” etc. are used herein whenidentifying multiple elements or components which may be referred toseparately. Unless otherwise specified or understood based on theircontext of use, such descriptors are not intended to impute any meaningof priority, physical order or arrangement in a list, or ordering intime but are merely used as labels for referring to multiple elements orcomponents separately for ease of understanding the disclosed examples.In some examples, the descriptor “first” may be used to refer to anelement in the detailed description, while the same element may bereferred to in a claim with a different descriptor such as “second” or“third.” In such instances, it should be understood that suchdescriptors are used merely for ease of referencing multiple elements orcomponents.

DETAILED DESCRIPTION

As used herein, the term “media” includes any type of content and/oradvertisement delivered via any type of distribution medium. Thus, mediaincludes television programming or advertisements, radio programming oradvertisements, movies, web sites, streaming media, etc.

Example methods, apparatus, and articles of manufacture disclosed hereinmonitor media presentations at media devices. Such media devices mayinclude, for example, Internet-enabled televisions, personal computers,Internet-enabled mobile handsets (e.g., a smartphone), tablet computers(e.g., an iPad®), digital media players (e.g., a Roku® media player, aSlingbox®, etc.), etc.

Example methods, apparatus, and articles of manufacture disclosed hereincollect media monitoring information from various media devices. In someexamples, media monitoring information is aggregated to determineownership and/or usage statistics of media devices, determine the mediapresented, determine audience ratings, determine relative rankings ofusage and/or ownership of media devices, determine types of uses ofmedia devices (e.g., whether a device is used for browsing the Internet,streaming media from the Internet, etc.), and/or determine other typesof media device information. In examples disclosed herein, monitoringinformation includes, but is not limited to, media identifyinginformation (e.g., media-identifying metadata, codes, signatures,watermarks, and/or other information that may be used to identifypresented media), application usage information (e.g., an identifier ofan application, a time and/or duration of use of the application, arating of the application, etc.), and/or user-identifying information(e.g., demographic information, a user identifier, a panelistidentifier, a username, etc.).

In some examples, audio watermarking is used to identify media such astelevision broadcasts, radio broadcasts, advertisements (televisionand/or radio), downloaded media, streaming media, prepackaged media,etc. Existing audio watermarking techniques identify media by embeddingone or more audio codes (e.g., one or more watermarks), such as mediaidentifying information and/or an identifier that may be mapped to mediaidentifying information, into an audio and/or video component. In someexamples, the watermark is embedded in the audio or video component sothat the watermark is hidden.

As used herein, the terms “code” or “watermark” are used interchangeablyand are defined to mean any identification information (e.g., anidentifier) that may be inserted or embedded in the audio or video ofmedia (e.g., a program or advertisement) for the purpose of identifyingthe media or for another purpose such as tuning (e.g., a packetidentifying header).

To identify watermarked media, the watermark(s) are extracted and usedto access a table of reference watermarks that are mapped to mediaidentifying information. In some examples, media monitoring companiesprovide watermarks and watermarking devices to media providers withwhich to encode their media source feeds. In some examples, if a mediaprovider provides multiple media source feeds (e.g., ESPN and ESPN 2,etc.), a media provider can provide a different watermark for each mediasource feed. In some examples, a media provider could encode a mediasource feed with an incorrect watermark (e.g., a watermark meant forESPN could accidentally be encoded on ESPN2, etc.). In this example,crediting using only watermarking could result in the wrong media sourcefeed being credited.

In some examples, signature matching is utilized to identify media.Unlike media monitoring techniques based on codes and/or watermarksincluded with and/or embedded in the monitored media, fingerprint orsignature-based media monitoring techniques generally use one or moreinherent characteristics of the monitored media during a monitoring timeinterval to generate a substantially unique proxy for the media. Such aproxy is referred to as a signature or fingerprint, and can take anyform (e.g., a series of digital values, a waveform, etc.) representativeof any aspect(s) of the media signal(s) (e.g., the audio and/or videosignals forming the media presentation being monitored). A signature maybe a series of signatures collected in series over a time interval. Agood signature is repeatable when processing the same mediapresentation, but is unique relative to other (e.g., different)presentations of other (e.g., different) media. Accordingly, the terms“fingerprint” and “signature” are used interchangeably herein and aredefined herein to mean a proxy for identifying media that is generatedfrom one or more inherent characteristics of the media.

Signature-based media monitoring generally involves determining (e.g.,generating and/or collecting) signature(s) representative of a mediasignal (e.g., an audio signal and/or a video signal) output by amonitored media device and comparing the monitored signature(s) to oneor more references signatures corresponding to known (e.g., reference)media source feeds. Various comparison criteria, such as across-correlation value, a Hamming distance, etc., can be evaluated todetermine whether a monitored signature matches a particular referencesignature. When a match between the monitored signature and a referencesignature is found, the monitored media can be identified ascorresponding to the particular reference media represented by thereference signature that matched with the monitored signature. In someexamples, signature matching is based on sequences of signatures suchthat, when a match between a sequence of monitored signatures and asequence of reference signatures is found, the monitored media can beidentified as corresponding to the particular reference mediarepresented by the sequence of reference signatures that matched thesequence of monitored signatures. Because attributes, such as anidentifier of the media, a presentation time, a broadcast channel, etc.,are collected for the reference signature(s), these attributes may thenbe associated with the monitored media whose monitored signature matchedthe reference signature(s).

In some examples, a user may interact with multiple media devices at atime. For example, a user may be watching media on a set device (e.g.,on a television set) and interacting with media on a mobile device(e.g., on a smartphone). In such examples, it is difficult to determinewhich media (e.g., on the set device or on the mobile device) the useris paying attention to just from the media monitoring information. Forexample, the media monitoring information from the set device mayindicate that the user was watching an advertisement presented via theset device during a period time, and the media monitoring informationfrom the mobile device may indicate that the user was watching othermedia presented via the mobile device during the same period of time.However, in such examples, the media monitoring information does notindicate if the user is looking at the media on the set device orlooking at the media on the mobile device during the period of time.Thus, the media monitoring information may provide inaccurateinformation related to media exposure.

Example methods, apparatus, and articles of manufacture disclosed hereindetermine whether the user's attention is on the mobile device duringspecific periods of time. In some examples, the set device signals tothe mobile device to take an action during a time period (e.g., duringan advertisement, a specific broadcasting event such as a politicaldebate, etc.). Examples disclosed herein provide instructions from theset device to a mobile device that determines if the user's attention ison the mobile device. In some examples, a camera on the mobile device isturned on to detect the face of a user to determine the orientation ofthe face and/or the gaze of the user, which may indicate if the user'sattention is on the mobile device. In some examples, the mobile devicecan detect other user interactions with the mobile device such as, forexample, touch on a screen, external device connections (e.g., use ofheadphones, ear buds, etc.), application launches, orientation and/orpositioning of the mobile device, etc. to determine if the user'sattention is on the mobile device. Examples disclosed herein provideuser attention data results with the media monitoring information fortime periods of interest.

FIG. 1 illustrates an example environment in which mobile deviceattention is detected in accordance with the teachings of thisdisclosure. The example environment 100 of FIG. 1 includes an exampleset device 105, an example network 110, an example mobile device 115, anexample network device 120, an example internet 125, and an example datacenter 130. The example set device 105 includes an example set meter135. The example mobile device includes an example mobile meter 140, anexample interval timer 145, an example attention determiner 150, and anexample camera 155.

In the illustrated example of FIG. 1 , the example set device 105 isused to access and view different media. The example set device 105 canbe implemented with any device or combinations of devices that are ableto connect to media such as, for example, a smart television (TV), aset-top box (STB), a game console, a digital video recorder (DVR), anApple TV, a Roku device, YouTube TV, an Amazon fire device, otherover-the-top (OTT) devices, etc., or any combination thereof. Theexample set device 105 is in proximity to the mobile device 115. Forexample, the set device 105 and the mobile device may be in the sameroom of a house or other building.

The example set meter 135 of the illustrated example of FIG. 1 collectsmedia monitoring information from the example set device 105. In someexamples, the set meter 135 is associated with (e.g., installed on,coupled to, etc.) the set device 105. For example, an associated setdevice 105 presents media (e.g., via a display, etc.) while, in otherexamples, the associated set device 105 presents the media on separatemedia presentation equipment (e.g., speakers, a display, etc.). In suchexamples, the set meter 135 may have a direct connection (e.g., physicalconnection) to the set device 105 to be monitored, and/or may beconnected wirelessly (e.g., via Wi-Fi, via Bluetooth, etc.) to the setdevice 105 to be monitored. The example set meter 135 identifies eventsin the media and/or the media monitoring information that are ofinterest. For example, the example set meter 135 can identify that anadvertisement commercial of interest is being presented or is scheduledto be presented on the example set device 105 based on the collectedmedia monitoring information and/or a schedule of media to be presented.The example set meter 135 can use any content identification technologyto identify media events of interest such as, for example, automaticcontent recognition (ACR), watermarks, signatures, etc.

The example set meter 135 transmits instructions to the example mobilemeter 140 when the example set meter 135 identifies a media event ofinterest from the media and/or the media monitoring information. Theexample set meter 135 can transmit instructions to the example mobilemeter 140 using any communication interface such as, for example, Wi-Fi,Bluetooth, cellular interfaces, etc. However, other means oftransmitting instructions may additionally and/or alternatively be used.In some examples, the instructions can be a control start signal whenthe beginning of a media event of interest is first identified in themedia and/or the media monitoring information, and a control end signalwhen the end of a media event of interest is identified in the mediaand/or the media monitoring information. In some examples, the set meter135 can receive user attention data from the example mobile meter 140.In such examples, the set meter 135 may transmit the collected mediamonitoring information and the user attention data to/via the exampleinternet 125. In the illustrated example of FIG. 1 , the set meter 135transmits instructions to one mobile meter on one mobile device (e.g.,the mobile meter 140 and the mobile device 115), and the set meter 135receives the user attention data from the one mobile meter 140 on themobile device 115. However, in some examples, the set meter 135 maytransmit the instructions to multiple mobile meters on one or moremobile devices on the same network and/or other networks in a household.In such examples, the set meter 135 may receive user attention data fromthe multiple mobile meters on the one or more mobile devices. In suchexamples, the set meter 135 may transmit the collected media monitoringinformation and the collective user attention data from the multiplemobile meters to/via the example internet 125.

The example network 110 of the illustrated example of FIG. 1 providescommunication between the example set meter 135 and the example mobilemeter 140. The example set meter 135 transmits instructions to theexample mobile meter 140 using the example network 110. The examplemobile meter 140 uses the example network 110 to transmit user attentiondata to the example set meter 135. In some examples, the set meter 135transmits the collected media monitoring information and the exampleuser attention data to the example internet 125 using the examplenetwork 110. The example network 110 is implemented as a local areanetwork (LAN). However, any other type of network may additionallyand/or alternatively be used such as, for example, a wide area network(WAN), a wireless local area network (WLAN), a storage area network(SAN), etc.

The example mobile device 115 of the illustrated example of FIG. 1 isused to access and view different media and information. The examplemobile device 115 can be implemented with any device or combinations ofdevices that are able to connect to the example network 110 and receivethe instructions from the example set meter 135 such as, for example, asmartphone, a laptop, a tablet, etc., or any combination thereof.

The example mobile meter 140 of the illustrated example of FIG. 1receives the instructions from the example set meter 135. In someexamples, the mobile meter 140 receives the control start signals andcontrol end signals from the example set meter 135. In some examples,the mobile meter 140 transmits user attention data to the example setmeter 135. In some examples, the mobile meter 140 associates the timestamp of when the user attention data was gathered and/or determinedprior to and/or when the example mobile meter 140 transmits the userattention data to the set meter 135. In some examples, the mobile meter140 is associated with (e.g., installed on, coupled to, etc.) the mobiledevice 115. For example, an associated mobile device 115 presents media(e.g., via a display, etc.) while, in other examples, the associatedmobile device 115 presents the media on separate media presentationequipment (e.g., speaker(s), a display, etc.). In such examples, themobile meter 140 may have a direct connection (e.g., physicalconnection) to the set device 105 to be monitored, and/or may beconnected wirelessly (e.g., via Wi-Fi, via Bluetooth, etc.) to themobile device 115 to be monitored.

The example interval timer 145 of the illustrated example of FIG. 1starts a timer when the example mobile meter 140 receives instructionsfrom the example set meter 135 and/or when the instructions indicate abeginning of a data collection time period. In some examples, theinterval timer 145 starts the timer when the example mobile meter 140receives a control start signal. In some examples, user attention datais collected periodically over the data collection time period of anevent of interest (e.g., time period between a control start signal anda control end signal). In such examples, the example interval timer 145sets a timer to a data collection interval for the desired periodic userattention data collection. For example, the data collection interval maybe five seconds (e.g., user attention data collected once every fiveseconds), ten seconds (e.g., user attention data collected once everyten seconds), thirty seconds (e.g., user attention data collected onceevery thirty seconds), etc. The example interval timer 145 runs thetimer over the data collection time period defined in the control startsignal, where the interval timer 145 segments the data collectionintervals throughout the data collection time period. In other examples,the user attention data is collected continuously or aperiodically overthe data collection time period. In such examples, the data collectioninterval would be set to zero (e.g., the interval timer 145 does notincrement, and the user attention data is collected continuously untilthe example mobile meter 140 receives the control end signal). In someexamples, the example interval timer 145 may receive a data collectiontime period from the instructions of the control start signal, whereuser attention data is only determined once during each data collectiontime period. In such examples, the data collection interval is the sameas the data collection time period. Also, the data collection timeperiod can be ten seconds, thirty seconds, one minute, etc. Other timeperiods may be used. The data collection time period may be differentfor different events of interest. For example, a first advertisementbreak during a television broadcast may be two minutes in duration and asecond advertisement break may be one minute in duration. In thisexample, the data collection time period for the first advertisementbreak may be two minutes in duration and the data collection time periodfor the second advertisement break may be one minute in duration.

In some examples, collecting the user attention data periodicallyincreases the battery efficiency for the example mobile device 115.Collecting the user attention data periodically requires less processorpower (e.g., the processor is used periodically for the datacollection), which increases the battery efficiency of the examplemobile device 115. In such examples, collecting the user attention dataperiodically also decreases the granularity of the user attention datadepending on the sampling rate determined by the collection period. Forexample, user attention data collected once every five seconds means theexample mobile meter 140 transmits only 20% of user attention dataduring a data collection time period. In other examples, collecting theuser attention data continuously decreases the battery efficiency forthe example mobile device 115. Collecting the user attention datacontinuously requires the processor to be run continuously for the datacollection, which causes the processor to use power from the batteryduring the entire data collection time period. When the processorconsumes power from the battery for continuous amounts of time, theoverall battery efficiency of the example mobile device 115 decreases.In such examples, collecting the user attention data continuouslyincreases the granularity of the user attention data. For example, userattention data collected continuously means the example mobile meter 140transmits 100% of the user attention data during a data collection timeperiod.

The example interval timer 145 activates the data collection intervaland monitors the amount of time that has passed during each datacollection interval. The example interval timer 145 waits until thetimer has reached the end of the data collection interval. In someexamples, the interval timer 145 restarts the timer when the mobilemeter 140 does not receive instructions to stop determining userattention (e.g., a control end signal). For example, the data collectiontime period for an example advertisement may be one minute, and the datacollection interval may be ten seconds (e.g., user attention datacollected once every ten seconds). In this example, the interval timer145 restarts after each data collection interval (e.g., after tenseconds of the data collection time period, after twenty seconds of thedata collection time period, after thirty seconds of the data collectiontime period, after forty seconds of the data collection time period, andafter fifty seconds of the data collection time period.

The example attention determiner 150 of the illustrated example of FIG.1 determines user attention during each data collection interval. Insome examples, the attention determiner 150 determines user attentionusing the example camera 155 of the example mobile device 115 to detectuser gaze through face detection and face orientation detection. In someexamples, the attention determiner 150 determines user attention usingother forms of user interaction with the example mobile device 115. Forexample, the attention determiner 150 can determine user attention basedon if an application has launched on the mobile device 115, if the userinteracts with the screen of the example mobile device 115 (e.g., usertouch on the screen), and/or if the any external devices are connectedto the example mobile device 115 (e.g., headphones). In some examples,the attention determiner 150 can determine user attention based on anorientation of the mobile device 115 such as, for example, an angle oforientation of the mobile device 115. The example attention determiner150 transmits the user attention data to the example mobile meter 140.An example implementation of the attention determiner 150 is illustratedin FIG. 2 , which is described in further detail below.

The example network device 120 of the illustrated example of FIG. 1provides communication between the example network 110 and the exampleinternet 125. The example network device 120 provides the mediamonitoring information and the user attention data from the examplenetwork 110 to the example internet 125. The example network device 120is implemented as a network device such as, for example, a modem.However, any other network devices may additionally and/or alternativelybe used.

The example internet 125 of the illustrated example of FIG. 1 providescommunication between the example network device 120, and the exampledata center 130. The example internet 125 provides communication of themedia monitoring information and the user attention data from theexample network device 120 and the example data center 130. The exampleinternet 125 is implemented as a public network such as, for example,the Internet. However, any other type of networks (e.g., wireless,mobile cellular, etc.) which may be public or private, and anycombination thereof may additionally and/or alternatively be used.

The example data center 130 of the illustrated example of FIG. 1collects media monitoring information and user attention data from theexample internet 125. In some examples, the data center 130 isassociated with an AME. In some examples, the data center 130 can be aphysical processing center (e.g., a central facility of the AME, etc.).Additionally or alternatively, the data center 130 can be implementedvia a cloud service (e.g., Amazon Web Services (AWS), etc.). The exampledata center 130 can further store and process media monitoringinformation and user attention data. In some examples, the data center130 associates the media monitoring information with the user attentiondata that was collected at the same time. In some examples, the userattention data may be collected by multiple mobile meters on differentmobile devices. In such examples, the data center 130 can process thecollective user attention data from the multiple mobile meters todetermine trends on what media is more captivating to users in ahousehold.

FIG. 2 is a block diagram representative of the example attentiondeterminer 150 of FIG. 1 . The example attention determiner 150 of FIG.2 includes an example camera controller 210, an example camera datagenerator 215, an example interaction determiner 220, and an exampleattention data generator 225.

The example camera controller 210 of the illustrated example of FIG. 2determines if the example mobile device 115 includes a camera 155. Theexample camera controller 210 activates the camera 155 of the examplemobile device 115 when the example camera controller 210 determines thatthere is a camera available, upon receipt of a control start signal,and/or at the beginning of a data collection period and/or interval. Insome examples, the example camera controller 210 activates the camera155 of the example mobile device 115 in accordance with the datasampling or collection periodicity identified in the control startsignal. For example, the camera controller 210 can activate the camera155 once during the data collection interval, multiple times,continuously, etc. When there is no camera, the attention determiner 150can determine user attention via other methods disclosed herein.

The example camera data generator 215 of the illustrated example of FIG.2 determines if the attention of the user is on the example mobiledevice 115 using the camera 155 on the example mobile device 115. Theexample camera data generator 215 determines if the attention of a useris on the example mobile device 115 by determining if the user's headand/or face is detected by the camera 155. In some examples, the examplecamera data generator 215 detects the user's head and/or face byidentifying general features of a face or head. For example, the examplecamera 155 may capture a user's eyes and nose. In this example, thecamera data generator 215 detects that this capture is of a user's headand face because it includes the common features of a face (e.g., eyesand nose). However, other techniques of detecting a user's head and/orface may additionally and/or alternatively be used. In some examples,the camera data generator 215 determines the orientation of the user'shead and/or face when the user's head and/or face is detected by thecamera 155. The example camera data generator 215 determines if theattention of a user is directed to the example mobile device 115 whenthe camera data generator 215 determines that the user's face is pointedtoward the example mobile device 115. In some examples, the camera datagenerator 215 can determine if the orientation of the user's face istoward the example mobile device 115 by determining if the eyes arevisible and directed toward the camera 155. However, other techniques ofdetermining user face orientation may additionally and/or alternativelybe used. Additionally, the example camera data generator 215 determinesif the attention of a user is on the example mobile device 115 bydetermining if the user's gaze is detected by the camera 155. In someexamples, the camera data generator 215 determines the gaze of the userwhen the centers (e.g., pupils) of the user's eyes are detected by thecamera 155. However, other techniques of determining user gaze mayadditionally and/or alternatively be used.

In some examples, the example interaction determiner 220 of theillustrated example of FIG. 2 determines user interactions with theexample mobile device 115. In some examples, the interaction determiner220 determines one or more user interactions with the mobile device 115when the camera controller 210 determines that the mobile device 115does not have a camera available. In some examples, the interactiondeterminer 220 determines user interactions with the mobile device 115in addition to the user gaze data determined by the camera datagenerator 215. The example interaction determiner 220 determines if theattention of the user is on the example mobile device 115 by determiningif any user interactions have occurred in the data collection interval.In some examples, the interaction determiner 220 determines a userinteraction by determining if any applications were launched on themobile device 115 (e.g., the user launches an email application on themobile device 115, the user launches a social media application on themobile device 115, etc.). In some examples, the interaction determiner220 determines a user interaction by determining if any userinteractions were detected on the screen of the mobile device 115 (e.g.,user touch on the screen). In some examples, the interaction determiner220 determines a user interaction by determining if any external deviceswere connected to the mobile device 115 (e.g. headphones). In someexamples, the interaction determiner 220 determines a user interactionby determining the orientation of the mobile device 115 such as, forexample, an angle of orientation of the mobile device 115.

The example attention data generator 225 of the illustrated example ofFIG. 2 generates the user attention data based on the outputs of theexample camera data generator 215 and/or the example interactiondeterminer 220. The example attention data generator 225 generates theuser attention data to identify if the user's attention is on theexample mobile device 115 during the data collection intervals. In someexamples, the attention data generator 225 generates the user attentiondata based on a combination of the outputs of the example camera datagenerator 215 and the example interaction determiner 220. In someexamples, the attention data generator 225 generates the user attentiondata based only on the output of the example camera data generator 215.In some examples, the attention data generator 225 generates the userattention data based only on the output of the example interactiondeterminer 220. For example, if the example mobile device 115 does nothave the example camera 155, the example attention data generator 225generates the user attention data based only on the output of theexample interaction determiner 220. For example, the attention datagenerator 225 generates the user attention data based on the applicationlaunch data, the touch on the screen of the mobile device 115 data, theexternal device connection data, and/or the orientation of the mobiledevice 115. In some examples, the attention data generator 225 generatesthe user attention data based on only one of the above outputs of theexample interaction determiner 220.

In some examples, the attention determiner 150 has a hierarchy of dataused to determine attention data. For example, the attention determiner150 first uses user gaze data to determine attention data. Thesecond-most important or informative data may be application launchdata; third-most important or informative data may be screen touch data;the fourth-most important or informative data may be external deviceconnection data, and the fifth-most important or informative data may bedata related to the orientation of the mobile device. In some examples,combinations of data may also be ranked in the hierarchy. In otherexamples, other hierarchical arrangements may be used to determine theimportance and/or informative value of the data. In some examples,different weights may be applied to one or more of the data categories.In some examples, the hierarchy and/or weights may change depending onthe media event of interest. For example, user gaze data may be weightedmore heavily for a visual media event of interest and less heavily foran audio media event of interest.

In some examples, the attention data generator 225 generates binary userattention data. For example, the user attention data may contain a “1”that indicates the user's attention was on the example mobile device 115and a “0” that indicates the user's attention was not on the examplemobile device 115. In some examples, the attention data generator 225generates user attention data with user activity descriptions. Forexample, the user attention data may contain descriptions of what theuser was doing on the example mobile device 115 when the user'sattention was determined to be on the example mobile device 115. Forexample, the user attention data may contain the description of“launched Facebook application” for the mobile device 115 during a datacollection time period. The example attention data generator 225provides the example mobile meter 140 of FIG. 1 with the example userattention data during the data collection time period(s).

While an example manner of implementing the example set device 105 isillustrated in FIG. 1 , one or more of the elements, processes and/ordevices illustrated in FIG. 1 may be combined, divided, re-arranged,omitted, eliminated and/or implemented in any other way. Further, theexample set meter 135 and/or, more generally, the example set device 105of FIG. 1 may be implemented by hardware, software, firmware and/or anycombination of hardware, software and/or firmware. Thus, for example,any of the example set meter 135 and/or, more generally, the example setdevice 105 could be implemented by one or more analog or digitalcircuit(s), logic circuits, programmable processor(s), programmablecontroller(s), graphics processing unit(s) (GPU(s)), digital signalprocessor(s) (DSP(s)), application specific integrated circuit(s)(ASIC(s)), programmable logic device(s) (PLD(s)) and/or fieldprogrammable logic device(s) (FPLD(s)). When reading any of theapparatus or system claims of this patent to cover a purely softwareand/or firmware implementation, at least one of the example set meter135 is/are hereby expressly defined to include a non-transitory computerreadable storage device or storage disk such as a memory, a digitalversatile disk (DVD), a compact disk (CD), a Blu-ray disk, etc.including the software and/or firmware. Further still, the example setdevice 105 of FIG. 1 may include one or more elements, processes and/ordevices in addition to, or instead of, those illustrated in FIG. 1 ,and/or may include more than one of any or all of the illustratedelements, processes and devices. As used herein, the phrase “incommunication,” including variations thereof, encompasses directcommunication and/or indirect communication through one or moreintermediary components, and does not require direct physical (e.g.,wired) communication and/or constant communication, but ratheradditionally includes selective communication at periodic intervals,scheduled intervals, aperiodic intervals, and/or one-time events.

A flowchart representative of example hardware logic, machine readableinstructions, hardware implemented state machines, and/or anycombination thereof for implementing the example set device 105 of FIG.1 is shown in FIG. 3 . The machine readable instructions may be one ormore executable programs or portion(s) of an executable program forexecution by a computer processor such as the processor 812 shown in theexample processor platform 800 discussed below in connection with FIG. 8. The program may be embodied in software stored on a non-transitorycomputer readable storage medium such as a CD-ROM, a floppy disk, a harddrive, a DVD, a Blu-ray disk, or a memory associated with the processor812, but the entire program and/or parts thereof could alternatively beexecuted by a device other than the processor 912 and/or embodied infirmware or dedicated hardware. Further, although the example program isdescribed with reference to the flowchart illustrated in FIG. 3 , manyother methods of implementing the example set device 105 mayalternatively be used. For example, the order of execution of the blocksmay be changed, and/or some of the blocks described may be changed,eliminated, or combined. Additionally or alternatively, any or all ofthe blocks may be implemented by one or more hardware circuits (e.g.,discrete and/or integrated analog and/or digital circuitry, an FPGA, anASIC, a comparator, an operational-amplifier (op-amp), a logic circuit,etc.) structured to perform the corresponding operation withoutexecuting software or firmware.

While an example manner of implementing the example mobile device 115 ofFIG. 1 is illustrated in FIGS. 1 and 2 , one or more of the elements,processes and/or devices illustrated in FIGS. 1 and 2 may be combined,divided, re-arranged, omitted, eliminated and/or implemented in anyother way. Further, the example mobile meter 140, the example intervaltimer 145, the example attention determiner 150, the example cameracontroller 210, the example camera data generator 215, the exampleinteraction determiner 220, the example attention data generator 225and/or, more generally, the example mobile device 115 of FIG. 1 may beimplemented by hardware, software, firmware and/or any combination ofhardware, software and/or firmware. Thus, for example, any of theexample mobile meter 140, the example interval timer 145, the exampleattention determiner 150, the example camera controller 210, the examplecamera data generator 215, the example interaction determiner 220, theexample attention data generator 225 and/or, more generally, the examplemobile device 115 could be implemented by one or more analog or digitalcircuit(s), logic circuits, programmable processor(s), programmablecontroller(s), GPU(s), DSP(s), ASIC(s), PLD(s) and/or FPLD(s). Whenreading any of the apparatus or system claims of this patent to cover apurely software and/or firmware implementation, at least one of theexample mobile meter 140, the example interval timer 145, the exampleattention determiner 150, the example camera controller 210, the examplecamera data generator 215, the example interaction determiner 220,and/or the example attention data generator 225 is/are hereby expresslydefined to include a non-transitory computer readable storage device orstorage disk such as a memory, a DVD, a CD, a Blu-ray disk, etc.including the software and/or firmware. Further still, the examplemobile device 115 of FIG. 1 may include one or more elements, processesand/or devices in addition to, or instead of, those illustrated in FIGS.1 and 2 , and/or may include more than one of any or all of theillustrated elements, processes and devices. As used herein, the phrase“in communication,” including variations thereof, encompasses directcommunication and/or indirect communication through one or moreintermediary components, and does not require direct physical (e.g.,wired) communication and/or constant communication, but ratheradditionally includes selective communication at periodic intervals,scheduled intervals, aperiodic intervals, and/or one-time events.

A flowchart representative of example hardware logic, machine readableinstructions, hardware implemented state machines, and/or anycombination thereof for implementing the example mobile device 115 ofFIG. 1 is shown in FIGS. 4, 5, 6, and 7 . The machine readableinstructions may be one or more executable programs or portion(s) of anexecutable program for execution by a computer processor such as theprocessor 912 shown in the example processor platform 900 discussedbelow in connection with FIG. 9 . The program may be embodied insoftware stored on a non-transitory computer readable storage mediumsuch as a CD-ROM, a floppy disk, a hard drive, a DVD, a Blu-ray disk, ora memory associated with the processor 912, but the entire programand/or parts thereof could alternatively be executed by a device otherthan the processor 912 and/or embodied in firmware or dedicatedhardware. Further, although the example program is described withreference to the flowchart illustrated in FIGS. 4, 5, 6, and 7 , manyother methods of implementing the example mobile device 115 mayalternatively be used. For example, the order of execution of the blocksmay be changed, and/or some of the blocks described may be changed,eliminated, or combined. Additionally or alternatively, any or all ofthe blocks may be implemented by one or more hardware circuits (e.g.,discrete and/or integrated analog and/or digital circuitry, an FPGA, anASIC, a comparator, an operational-amplifier (op-amp), a logic circuit,etc.) structured to perform the corresponding operation withoutexecuting software or firmware.

The machine readable instructions described herein may be stored in oneor more of a compressed format, an encrypted format, a fragmentedformat, a compiled format, an executable format, a packaged format, etc.Machine readable instructions as described herein may be stored as data(e.g., portions of instructions, code, representations of code, etc.)that may be utilized to create, manufacture, and/or produce machineexecutable instructions. For example, the machine readable instructionsmay be fragmented and stored on one or more storage devices and/orcomputing devices (e.g., servers). The machine readable instructions mayrequire one or more of installation, modification, adaptation, updating,combining, supplementing, configuring, decryption, decompression,unpacking, distribution, reassignment, compilation, etc. in order tomake them directly readable, interpretable, and/or executable by acomputing device and/or other machine. For example, the machine readableinstructions may be stored in multiple parts, which are individuallycompressed, encrypted, and stored on separate computing devices, whereinthe parts when decrypted, decompressed, and combined form a set ofexecutable instructions that implement a program such as that describedherein.

In another example, the machine readable instructions may be stored in astate in which they may be read by a computer, but require addition of alibrary (e.g., a dynamic link library (DLL)), a software development kit(SDK), an application programming interface (API), etc. in order toexecute the instructions on a particular computing device or otherdevice. In another example, the machine readable instructions may needto be configured (e.g., settings stored, data input, network addressesrecorded, etc.) before the machine readable instructions and/or thecorresponding program(s) can be executed in whole or in part. Thus, thedisclosed machine readable instructions and/or corresponding program(s)are intended to encompass such machine readable instructions and/orprogram(s) regardless of the particular format or state of the machinereadable instructions and/or program(s) when stored or otherwise at restor in transit.

The machine readable instructions described herein can be represented byany past, present, or future instruction language, scripting language,programming language, etc. For example, the machine readableinstructions may be represented using any of the following languages: C,C++, Java, C#, Perl, Python, JavaScript, HyperText Markup Language(HTML), Structured Query Language (SQL), Swift, etc.

As mentioned above, the example processes of FIGS. 3, 4, 5, 6 , and 7may be implemented using executable instructions (e.g., computer and/ormachine readable instructions) stored on a non-transitory computerand/or machine readable medium such as a hard disk drive, a flashmemory, a read-only memory, a CD, a DVD, a cache, a random-access memoryand/or any other storage device or storage disk in which information isstored for any duration (e.g., for extended time periods, permanently,for brief instances, for temporarily buffering, and/or for caching ofthe information). As used herein, the term non-transitory computerreadable medium is expressly defined to include any type of computerreadable storage device and/or storage disk and to exclude propagatingsignals and to exclude transmission media.

“Including” and “comprising” (and all forms and tenses thereof) are usedherein to be open ended terms. Thus, whenever a claim employs any formof “include” or “comprise” (e.g., comprises, includes, comprising,including, having, etc.) as a preamble or within a claim recitation ofany kind, it is to be understood that additional elements, terms, etc.may be present without falling outside the scope of the correspondingclaim or recitation. As used herein, when the phrase “at least” is usedas the transition term in, for example, a preamble of a claim, it isopen-ended in the same manner as the term “comprising” and “including”are open ended. The term “and/or” when used, for example, in a form suchas A, B, and/or C refers to any combination or subset of A, B, C such as(1) A alone, (2) B alone, (3) C alone, (4) A with B, (5) A with C, (6) Bwith C, and (7) A with B and with C. As used herein in the context ofdescribing structures, components, items, objects and/or things, thephrase “at least one of A and B” is intended to refer to implementationsincluding any of (1) at least one A, (2) at least one B, and (3) atleast one A and at least one B. Similarly, as used herein in the contextof describing structures, components, items, objects and/or things, thephrase “at least one of A or B” is intended to refer to implementationsincluding any of (1) at least one A, (2) at least one B, and (3) atleast one A and at least one B. As used herein in the context ofdescribing the performance or execution of processes, instructions,actions, activities and/or steps, the phrase “at least one of A and B”is intended to refer to implementations including any of (1) at leastone A, (2) at least one B, and (3) at least one A and at least one B.Similarly, as used herein in the context of describing the performanceor execution of processes, instructions, actions, activities and/orsteps, the phrase “at least one of A or B” is intended to refer toimplementations including any of (1) at least one A, (2) at least one B,and (3) at least one A and at least one B.

As used herein, singular references (e.g., “a”, “an”, “first”, “second”,etc.) do not exclude a plurality. The term “a” or “an” entity, as usedherein, refers to one or more of that entity. The terms “a” (or “an”),“one or more”, and “at least one” can be used interchangeably herein.Furthermore, although individually listed, a plurality of means,elements or method actions may be implemented by, e.g., a single unit orprocessor. Additionally, although individual features may be included indifferent examples or claims, these may possibly be combined, and theinclusion in different examples or claims does not imply that acombination of features is not feasible and/or advantageous.

FIG. 3 is a flowchart illustrating an example process 300 that isrepresentative of machine-readable instructions which may be executed toimplement the example set meter 135 of FIG. 1 . The program of FIG. 3includes the example set meter 135 collecting the media monitoringinformation (block 310). In some example, the set meter 135 collects themedia monitoring information from the set device 105. The example setmeter 135 identifies the start of a media event of interest (block 315).In some examples, the set meter 135 identifies the start of a mediaevent of interest using content identification technology such as, forexample, ACR, watermarking, signatures, etc. For example, the set meter135 may obtain and decode a watermark embedded in a stream of media. Thewatermark provides information related to the media and may be used bythe set meter 135 to identify that the media associated with thewatermark is an advertisement, which may be a media event of interest.

If the example set meter 135 identifies the start of a media event ofinterest, the process 300 continues and the set meter 135 transmits acontrol start signal (block 320). If the example set meter 135 does notidentify the start of a media event of interest, the process 300 returnsand the example set meter 135 collects the media monitoring information(block 310).

To transmit a control start signal (block 320), the set meter 135, insome examples, transmits the control start signal to the mobile meter140 using the network 110. The set meter 135 transmits the control startsignal using any communication interfaces such as, for example, Wi-Fi,Bluetooth, cellular interfaces, etc.

The example set meter 135 receives user attention data from the examplemobile meter 140 (block 325). In some examples, the set meter 135receives the user attention data from the example mobile meter 140 usingthe example network 110. In some examples, the set meter 135 associatesthe user attention data with the media monitoring information that wasgenerated and/or collected at the same time.

The example set meter 135 identifies the end of the media event ofinterest (block 330). In some examples, the set meter 135 identifies theend of a media event of interest using any content identificationtechnology such as, for example, ACR, watermarking, signatures, etc. Forexample, the set meter 135 may obtain and decode a watermark embedded ina stream of media. The watermark provides information related to themedia and may be used by the set meter 135 to identify that the mediaassociated with the watermark is not an advertisement, which may be themedia event of interest. If the example set meter 135 identifies the endof the media event of interest, the process 300 continues and the setmeter 135 transmits a control end signal (block 335). If the example setmeter 135 does not identify the end of the media event of interest, theprocess 300 returns and the set meter 135 receives (e.g., continues toreceive) the user attention data from the example mobile meter 140(block 325). In some examples, the set meter 135 may not receive theuser attention data from the example mobile meter 140 during the mediaevent of interest. For example, the mobile meter 140 may not transmitthe user attention data until after the set meter 135 identifies the endof the media event of interest. In this example, the mobile meter 140may not transmit the user attention data until waiting a period of timeafter the set meter 135 identifies the end of the media event ofinterest.

To transmit the control end signal (block 335), the set meter 135, insome examples, transmits the control end signal to the mobile meter 140using the network 110. The set meter 135 transmits the control endsignal using any communication interfaces such as, for example, Wi-Fi,Bluetooth, cellular interfaces, etc. The example set meter 135 transmitsthe media monitoring information and the user attention data (block340). The example set meter 135 transmits the collected media monitoringinformation and the user attention data for the event of interest to theexample data center 130. In some examples, the set meter 135 transmitsthe media monitoring information and the user attention data to the datacenter 130 used the network 110, network device 120, and the internet125.

In some examples, the example process 300 include the set meter 135determining if there is another media event of interest (block 345). Ifthere is another media event of interest, the process 300 continues andthe set meter 135 transmits the control start signal (block 320). Ifthere is no additional media event of interest, the process 300 ends.

FIG. 4 is a flowchart illustrating an example process 400 that isrepresentative of machine readable instructions which may be executed toimplement the example mobile device 115 of FIG. 1 . The program of FIG.4 includes the example mobile meter 140 receiving the control startsignal from the example set meter 135 (block 410). In some examples, themobile meter 140 receives the control start signal from the example setmeter 135 using the network 110. If the example mobile meter 140receives the control start signal from the example set meter 135, theinterval timer 145 starts timer (block 415). If the example mobile meter140 does not receive the control signal from the example set meter 135,the process 400 sits idle until a control start signal is received(block 410).

In some examples, the example interval timer 145 starts the timer (block415) in accordance with a data collection interval for the datacollection time period identified in the control start signal. The datacollection time period can be ten seconds, thirty seconds, one minute,etc. The example interval timer 145 activates a timer that keeps trackof the data collection interval. In some examples, the user attentiondata is collected periodically during each data collection time period.In such examples, the example interval timer 145 sets a timer to a datacollection interval for the desired periodic user attention datacollection. For example, the data collection interval may be fiveseconds (e.g., user attention data collected once every five seconds),ten seconds (e.g., user attention data collected once every tenseconds), thirty seconds (e.g., user attention data collected once everythirty seconds), etc. The example interval timer 145 runs the timer overthe data collection time period defined in the control start signal,where the interval timer 145 segments the data collection intervalsthroughout the data collection time period. In some example, the userattention data is collected continuously during each data collectiontime period. In such examples, the data collection interval would be setto zero (e.g., the interval timer 145 does not increment, and the userattention data is collected continuously until the example mobile meter140 receives the control end signal). In some examples, the userattention data is collected once during each data collection timeperiod. In such examples, the data collection interval is the same asthe data collection time period.

The example attention determiner 150 determines user attention (block420). In some examples, the attention determiner 150 can determine userattention using the camera 155 of the example mobile device 115 todetect user gaze through face detection and face orientation detection.In some examples, the attention determiner 150 can determine userattention using other forms of user interaction with the example mobiledevice 115. For example, the attention determiner 150 can determine userattention based on if an application has launched on the mobile device115, if the user interacts with the screen of the example mobile device115 (e.g., user touch on the screen), and/or if the any external devicesare connected to the example mobile device 115 (e.g., headphones). Asdescribed in further detail below, the example flowchart 420 of FIG. 5represents example instructions that may be implemented to determine theuser attention.

The example mobile meter 140 transmits the user attention data from theexample attention determiner 150 (block 425). In some examples, themobile meter 140 transmits user attention data to the example set meter135. In some examples, the mobile meter 140 associates the time stampthat the user attention data was determined when the example mobilemeter 140 transmits the user attention data to the set meter 135. Theexample interval timer 145 waits for the timer to reach the time of thedata collection interval (block 430). The example interval timer 145monitors the amount of time that has passed on the timer until the timerreaches the amount of time for the data collection interval. In someexamples, the mobile meter 140 may not transmit the user attention dataduring the data collection time period. For example, the mobile meter140 may not transmit the user attention data until after the mobilemeter 140 receives a control end signal. In this example, the mobilemeter 140 may not transmit the user attention data until waiting aperiod of time after the mobile meter 140 receives a control end signal.

The example mobile meter 140 receives a control end signal from theexample set meter 135 (block 435). In some examples, the mobile meter140 receives the control end signal from the example set meter 135 usingthe network 110. If the example mobile meter 140 does not receive thecontrol end signal from the example set meter 135, the example intervaltimer 145 restarts the timer (block 415). In some examples, the intervaltimer 145 restarts the timer when the mobile meter 140 does not receivea control end signal. For example, the data collection time period foran example advertisement of interest may be one minute, and the datacollection interval may be ten seconds (e.g., user attention datacollected once every ten seconds). In this example, the interval timer145 restarts the timer after each data collection interval (e.g., afterten seconds of the data collection time period, after twenty seconds ofthe data collection time period, after thirty seconds of the datacollection time period, after forty seconds of the data collection timeperiod, and after fifty seconds of the data collection time period. Ifthe example mobile meter 140 receives the control end signal from theexample set meter 135, the process 400 ends.

FIG. 5 is a flowchart illustrating a process 420 that is representativeof machine readable instructions which may be executed to implement anexample attention determiner 150 included in the example mobile device115 of FIG. 1 . The program of FIG. 5 begins execution at which theexample camera controller 210 determines if the example mobile device115 has a camera 155 (block 510). In some examples, the cameracontroller 210 determines if the mobile device 115 has a camera 155after the interval timer 145 of FIG. 1 indicates the start of a new datacollection interval. If the example camera controller 210 determinesthat the example mobile device 115 does have a camera 155, the process420 continues and the camera data generator 215 detects the userattention with the camera 155 (block 520). If the example cameracontroller 210 determines that the example mobile device 115 does nothave a camera, the process 420 continues and the interaction determiner220 detects the device interactions (block 530). In some examples, asdisclosed herein, the process 530 is performed when the mobile devicedoes have a camera.

The example camera data generator 215 detects the user attention withthe camera 155 (block 520). The example camera data generator 215determines user attention using the camera 155. As disclosed in furtherdetail below, the example flowchart 520 of FIG. 6 represents exampleinstructions that may be implemented to detect user attention with thecamera 155. After block 520, the process 420 continues and the attentiondata generator 225 generates the user attention data (block 540).

The example interaction determiner 220 detects the device interactions(block 530). In some examples, the interaction determiner 220 determinesuser interactions with the mobile device 115 when the camera controller210 determines that the mobile device 115 does not have a cameraavailable. In some examples, the interaction determiner 220 determinesany user interactions with the mobile device 115 in addition to the userattention data determined by the camera data generator 215. As describedin further detail below, the example flowchart 530 of FIG. 7 representsexample instructions that may be implemented to detect deviceinteractions. After block 530, the process 420 continues and theattention data generator 225 generates the user attention data (block540).

The example attention data generator 225 generates the user attentiondata (block 540). The example attention data generator 225 generates theuser attention data based on the outputs of the example camera datagenerator 215 and the example interaction determiner 220. The exampleattention data generator 225 generates the user attention data toidentify if the user's attention is on the example mobile device 115during each data collection interval determined by the example intervaltimer 145 of FIG. 1 . In some examples, the attention data generator 225generates binary user attention data. For example, the user attentiondata may contain a one that indicates the user's attention was on theexample mobile device 115 and a zero that indicates the user's attentionwas not on the example mobile device 115. In some examples, theattention data generator 225 generates user attention data with useractivity descriptions. For example, the user attention data may containdescriptions of what the user was doing on the example mobile device 115when the user's attention was determined to be on the example mobiledevice 115. After block 540, the process 420 completes and returns toprocess 400 of FIG. 4 .

FIG. 6 is a flowchart illustrating a process 520 that is representativeof machine readable instructions which may be executed to implement anexample camera controller 210 and an example camera data generator 215included in the example attention determiner 150 of FIG. 2 . The programof FIG. 6 includes the example camera controller 210 activating theexample mobile device 115 camera 155 (block 610).

The example camera data generator 215 determines if the user's face isdetected by the camera 155 (block 615). The example camera datagenerator 215 can use any face detection technology to determine if theuser's face is detected by the camera 155 on the example mobile device115. In some examples, the example camera data generator 215 detects theuser's head and/or face by identifying general features of a face orhead. For example, the example camera 155 may capture or detect a user'seyes and nose. In this example, the camera data generator 215 detectsthat this capture is of a user's head and face because the image orobject in the field of view of the camera includes the commons featuresof a face (e.g., eyes and nose). However, other techniques of detectinga user's head and/or face may additionally and/or alternatively be used.If the example camera data generator 215 does determine that the user'sface is detected by the camera 155, the process 520 continues and thecamera data generator determines the orientation of user's face (block620). If the example camera data generator 215 does not determine thatthe user's face is detected by the camera 155, the process 520 continuesand the camera data generator 215 determines the user attention is noton the example mobile device 115 (block 630).

The example camera data generator 215 determines if the orientation ofthe user's face is toward the example mobile device 115 (block 620). Insome examples, the camera data generator 215 can determine if theorientation of the user's face is toward the example mobile device 115by determining if the eyes are visible and directed toward the camera155. However, other techniques of determine user face orientation mayadditionally and/or alternatively be used. If the example camera datagenerator 215 determines that the orientation of the user's face istoward the example mobile device 115, the process 520 continues and thecamera data generator 215 determines if the user's gaze is on theexample mobile device 115 (block 625). If the example camera datagenerator 215 determines that the orientation of the user's face is nottowards the example mobile device 115, the process 520 continues and thecamera data generator 215 determines the user attention is not on theexample mobile device 115 (block 630).

The example camera data generator 215 determines if the user's gaze ison the mobile device 115 (block 625). In some examples, the camera datagenerator 215 determines the gaze of the user when the center(s) (e.g.,pupil(s)) of the user's eye(s) are detected by the camera 155. However,other techniques of determining user gaze may additionally and/oralternatively be used. If the example camera data generator 215determines that the user's gaze is on the example mobile device 115, theprocess 520 continues and the camera data generator 215 determines theuser attention is on the example mobile device 115 (block 635). If theexample camera data generator 215 determines that the user's gaze is noton the example mobile device 115, the process 520 continues and thecamera data generator 215 determines the user attention is not on theexample mobile device 115 (block 630).

The example camera data generator 215 determines that the user attentionis not on the example mobile device 115 (block 630). The example cameradata generator determines that the user attention is not on the examplemobile device 115 based on when the user's face is not detected by thecamera 155 on the example mobile device 115 and/or the orientation ofthe user's face is not towards the camera 155 on the example mobiledevice 115. After block 630, the process 520 completes and returns toprocess 420 of FIG. 5 .

The example camera data generator 215 determines that the user attentionis on the example mobile device 115 (block 635). The example camera datagenerator determines that the user attention is on the example mobiledevice 115 based on when the user's face is detected by the camera 155on the example mobile device 115 and the orientation of the user's faceis towards the camera 155 on the example mobile device 115. After block635, the process 520 completes and returns to process 420 of FIG. 5 .

FIG. 7 is a flowchart illustrating a process 530 that is representativeof machine readable instructions which may be executed to implement anexample interaction determiner 220 included in the example attentiondeterminer 150 of FIG. 2 . The program of FIG. 7 includes the exampleinteraction determiner 220 determining if any applications are launchedon the example mobile device 115 (block 710). In some examples, theinteraction determiner 220 determines if an application is launchedusing the processor of the mobile device 115. In such examples, theprocessor of the mobile device 115 is responsible for launchingapplications on the mobile device 115. In such examples, the interactiondeterminer 220 monitors the processor of the mobile device 115 forinstructions to execute a new application. However, other techniques fordetermining if an application is launched on the mobile device 115 mayadditionally and/or alternatively be used. If the example interactiondeterminer 220 determines that an application was launched on theexample mobile device 115, the process 530 continues and the interactiondeterminer 220 determines the user attention is on the mobile device 115(block 730). If the example interaction determiner 220 determines thatno applications were launched on the example mobile device 115, theprocess 530 continues and the interaction determine 220 determines if auser interaction is detected on the example mobile device 115 screen(block 715).

The example interaction determiner 220 determines if a user interactionis detected on the example mobile device 115 screen (block 715). In someexamples, a user interaction can be one or more touches on the screen ofthe example mobile device 115. In some examples, the interactiondeterminer 220 determines if a user interaction is detected on thescreen of the mobile device 115 by monitoring changes on the screen. Forexample, if the screen of the mobile device 115 is a capacitive touchscreen, the interaction determiner 220 monitors the screen of the mobiledevice 115 for a change in the electrical charge of the capacitivematerial of the screen caused by the contact of a user's finger. In someexamples, the screen of the mobile device 115 is a resistive touchscreen, and the interaction determiner 220 may monitor the screen of themobile device 115 for a change in the electrical resistance caused bythe pressure of a user's touch. However, other type of screen andtechniques for determining a user interaction with the screen of themobile device 115 may additionally and/or alternatively be used. If theexample interaction determiner 220 determines that a user interaction isdetected on the example mobile device 115 screen, the process 530continues and the interaction determiner 220 determines the userattention is on the mobile device 115 (block 730). If the exampleinteraction determiner 220 determines that no user interaction isdetected on the example mobile device 115 screen, the process 530continues and the interaction determiner 220 determines if an externaldevice is connected to the example mobile device 115 (block 720).

The example interaction determiner 220 determines if an external deviceis connected to the example mobile device 115 (block 720). In someexamples, an external device can be headphones, speakers, and/or otherauxiliary devices. In some examples, the interaction determiner 220determines if an external device is connected to the example mobiledevice 115 using the processor on the mobile device. In such examples,the processor of the mobile device 115 is responsible for detectingchanges in the circuit of an accessible connection point on the mobiledevice 115 (e.g., a headphone jack) as well as any Bluetooth connectionsmade to the mobile device 115. In such examples, the interactiondeterminer 220 monitors the processor of the mobile device 115 for anexecution of instructions for adding an external device connection(e.g., physical connection, Bluetooth connection, etc.). However, othertechniques for determining if an external device is connected to theexample mobile device 115 may additionally and/or alternatively be used.If the example interaction determiner 220 determines that an externaldevice is connected to the example mobile device 115, the process 530continues and the interaction determiner 220 determines the userattention is on the mobile device 115 (block 730). If the exampleinteraction determiner 220 determines that no external devices areconnected to the example mobile device 115, the process 530 continuesand the interaction determiner determines if the orientation of themobile device 115 changed (block 735).

The example interaction determiner 220 determines if the orientation ofthe example mobile device 115 changed (block 725). In some examples, theinteraction determiner 220 determines if the angle of the orientation ofthe mobile device 115 has changed and/or is within a threshold of anangle (e.g., the angle of the device is approximately forty-fivedegrees, the angle of the device is between approximately thirty degreesand approximately sixty degrees, the angle has increased, the angle hasdecreased, and/or other changes of orientation of the mobile device115). In some examples, the interaction determiner 220 determines if theorientation of the mobile device 115 changes using the sensor of themobile device 115. In such examples, the mobile device 115 may includegyroscope sensors and/or rotation sensor that determine the orientationof the mobile device 115. In such examples, the interaction determiner220 monitors the sensors of the mobile device 115 for any changes in theorientation data of the mobile device 115 (e.g., changes in anglemeasurements). However, other sensors and techniques for determining ifthe orientation of the mobile device 115 has changes may additionallyand/or alternatively be used. If the example interaction determiner 220determines that the orientation of the example mobile device 115changed, the process 530 continues and the interaction determiner 220determines the user attention is on the mobile device 115 (block 730).If the example interaction determiner 220 determines that theorientation of the example mobile device 115 did not change, the process530 continues and the interaction determiner determines the userattention is not on the mobile device 115 (block 735).

Though the process 530 is described with the interaction determiner 220sequentially performing the elements of blocks 710, 715, 720, and 725,there is no specific order required by the process 530. As noted above,the order of execution of the blocks may be rearranged. In addition, insome examples, the process 530 may perform one or more of the elementsof blocks 710, 715, 720, and 725 simultaneously.

The example interaction determiner 220 determines that the userattention is on the example mobile device 115 (block 730). The exampleinteraction determiner 220 determines that the user attention is on theexample mobile device 115 based on when applications are launched on theexample mobile device 115, user interactions are detected on the screenof the example mobile device 115, any external devices are connected tothe example mobile device 115, and/or orientation of the mobile devicechanges or matches a threshold orientation. After block 730, the process530 completes and returns to process 420 of FIG. 5 .

The example interaction determiner 220 determines that the userattention is not on the example mobile device 115 (block 735). Theexample interaction determiner 220 determines that the user attention isnot on the example mobile device 115 based on when no applications arelaunched on the example mobile device 115, no user interactions aredetected on the screen of the example mobile device 115, no externaldevices are connected to the example mobile device 115, and/or anorientation of the mobile device does not change or match a thresholdorientation. After block 735, the process 530 completes and returns toprocess 420 of FIG. 5 .

FIG. 8 is a block diagram of an example processor platform 800structured to execute the instructions of FIG. 3 to implement theexample set device 105 of FIG. 1 . The processor platform 800 can be,for example, a server, a personal computer, a workstation, aself-learning machine (e.g., a neural network), a mobile device (e.g., acell phone, a smart phone, a tablet such as an iPad™), a personaldigital assistant (PDA), an Internet appliance, a DVD player, a CDplayer, a digital video recorder, a Blu-ray player, a gaming console, apersonal video recorder, a set top box, a headset or other wearabledevice, or any other type of computing device.

The processor platform 800 of the illustrated example includes aprocessor 812. The processor 812 of the illustrated example is hardware.For example, the processor 812 can be implemented by one or moreintegrated circuits, logic circuits, microprocessors, GPUs, DSPs, orcontrollers from any desired family or manufacturer. The hardwareprocessor may be a semiconductor based (e.g., silicon based) device. Inthis example, the processor implements the example set meter 135.

The processor 812 of the illustrated example includes a local memory 813(e.g., a cache). The processor 812 of the illustrated example is incommunication with a main memory including a volatile memory 814 and anon-volatile memory 816 via a bus 818. The volatile memory 814 may beimplemented by Synchronous Dynamic Random Access Memory (SDRAM), DynamicRandom Access Memory (DRAM), RAMBUS® Dynamic Random Access Memory(RDRAM®) and/or any other type of random access memory device. Thenon-volatile memory 816 may be implemented by flash memory and/or anyother desired type of memory device. Access to the main memory 814, 816is controlled by a memory controller.

The processor platform 800 of the illustrated example also includes aninterface circuit 820. The interface circuit 820 may be implemented byany type of interface standard, such as an Ethernet interface, auniversal serial bus (USB), a Bluetooth® interface, a near fieldcommunication (NFC) interface, and/or a PCI express interface.

In the illustrated example, one or more input devices 822 are connectedto the interface circuit 820. The input device(s) 822 permit(s) a userto enter data and/or commands into the processor 812. The inputdevice(s) can be implemented by, for example, an audio sensor, amicrophone, a camera (still or video), a keyboard, a button, a mouse, atouchscreen, a track-pad, a trackball, isopoint and/or a voicerecognition system.

One or more output devices 824 are also connected to the interfacecircuit 820 of the illustrated example. The output devices 824 can beimplemented, for example, by display devices (e.g., a light emittingdiode (LED), an organic light emitting diode (OLED), a liquid crystaldisplay (LCD), a cathode ray tube display (CRT), an in-place switching(IPS) display, a touchscreen, etc.), a tactile output device, a printerand/or speaker. The interface circuit 820 of the illustrated example,thus, typically includes a graphics driver card, a graphics driver chipand/or a graphics driver processor.

The interface circuit 820 of the illustrated example also includes acommunication device such as a transmitter, a receiver, a transceiver, amodem, a residential gateway, a wireless access point, and/or a networkinterface to facilitate exchange of data with external machines (e.g.,computing devices of any kind) via a network 826. The communication canbe via, for example, an Ethernet connection, a digital subscriber line(DSL) connection, a telephone line connection, a coaxial cable system, asatellite system, a line-of-site wireless system, a cellular telephonesystem, etc.

The processor platform 800 of the illustrated example also includes oneor more mass storage devices 828 for storing software and/or data.Examples of such mass storage devices 828 include floppy disk drives,hard drive disks, compact disk drives, Blu-ray disk drives, redundantarray of independent disks (RAID) systems, and digital versatile disk(DVD) drives.

The machine executable instructions 832 of FIG. 3 may be stored in themass storage device 828, in the volatile memory 814, in the non-volatilememory 816, and/or on a removable non-transitory computer readablestorage medium such as a CD or DVD.

FIG. 9 is a block diagram of an example processor platform 900structured to execute the instructions of FIGS. 4, 5, 6, and 7 toimplement the example mobile device 115 of FIG. 1 . The processorplatform 900 can be, for example, a server, a personal computer, aworkstation, a self-learning machine (e.g., a neural network), a mobiledevice (e.g., a cell phone, a smart phone, a tablet such as an iPad™), apersonal digital assistant (PDA), an Internet appliance, a DVD player, aCD player, a digital video recorder, a Blu-ray player, a gaming console,a personal video recorder, a set top box, a headset or other wearabledevice, or any other type of computing device.

The processor platform 900 of the illustrated example includes aprocessor 912. The processor 912 of the illustrated example is hardware.For example, the processor 912 can be implemented by one or moreintegrated circuits, logic circuits, microprocessors, GPUs, DSPs, orcontrollers from any desired family or manufacturer. The hardwareprocessor may be a semiconductor based (e.g., silicon based) device. Inthis example, the processor implements the example mobile meter 140, theexample interval timer 145, the example attention determiner 150, theexample camera controller 210, the example camera data generator 215,the example interaction determiner, and the example attention datagenerator 225.

The processor 912 of the illustrated example includes a local memory 913(e.g., a cache). The processor 912 of the illustrated example is incommunication with a main memory including a volatile memory 914 and anon-volatile memory 916 via a bus 918. The volatile memory 914 may beimplemented by Synchronous Dynamic Random Access Memory (SDRAM), DynamicRandom Access Memory (DRAM), RAMBUS® Dynamic Random Access Memory(RDRAM®) and/or any other type of random access memory device. Thenon-volatile memory 916 may be implemented by flash memory and/or anyother desired type of memory device. Access to the main memory 914, 916is controlled by a memory controller.

The processor platform 900 of the illustrated example also includes aninterface circuit 920. The interface circuit 920 may be implemented byany type of interface standard, such as an Ethernet interface, auniversal serial bus (USB), a Bluetooth® interface, a near fieldcommunication (NFC) interface, and/or a PCI express interface.

In the illustrated example, one or more input devices 922 are connectedto the interface circuit 920. The input device(s) 922 permit(s) a userto enter data and/or commands into the processor 912. The inputdevice(s) can be implemented by, for example, an audio sensor, amicrophone, a camera (still or video), a keyboard, a button, a mouse, atouchscreen, a track-pad, a trackball, isopoint and/or a voicerecognition system.

One or more output devices 924 are also connected to the interfacecircuit 920 of the illustrated example. The output devices 924 can beimplemented, for example, by display devices (e.g., a light emittingdiode (LED), an organic light emitting diode (OLED), a liquid crystaldisplay (LCD), a cathode ray tube display (CRT), an in-place switching(IPS) display, a touchscreen, etc.), a tactile output device, a printerand/or speaker. The interface circuit 920 of the illustrated example,thus, typically includes a graphics driver card, a graphics driver chipand/or a graphics driver processor.

The interface circuit 920 of the illustrated example also includes acommunication device such as a transmitter, a receiver, a transceiver, amodem, a residential gateway, a wireless access point, and/or a networkinterface to facilitate exchange of data with external machines (e.g.,computing devices of any kind) via a network 926. The communication canbe via, for example, an Ethernet connection, a digital subscriber line(DSL) connection, a telephone line connection, a coaxial cable system, asatellite system, a line-of-site wireless system, a cellular telephonesystem, etc.

The processor platform 900 of the illustrated example also includes oneor more mass storage devices 928 for storing software and/or data.Examples of such mass storage devices 928 include floppy disk drives,hard drive disks, compact disk drives, Blu-ray disk drives, redundantarray of independent disks (RAID) systems, and digital versatile disk(DVD) drives.

The machine executable instructions 932 of FIGS. 4, 5, 6, and 7 may bestored in the mass storage device 928, in the volatile memory 914, inthe non-volatile memory 916, and/or on a removable non-transitorycomputer readable storage medium such as a CD or DVD.

From the foregoing, it will be appreciated that example methods,apparatus and articles of manufacture have been disclosed that allow foroptimization of determining user attention to media. The disclosedmethods, apparatus and articles of manufacture allow for more accuratecrediting of media exposure by determining if a user is paying attentionto media presented on a set device. The disclosed examples providecollective media exposure data to determine what media is morecaptivating for users. The disclosed methods, apparatus and articles ofmanufacture are accordingly directed to correcting erroneous audiencemeasurement data that may be automatically gathered from a set-top boxor other audience measurement meter. As disclosed herein, these examplesdetect a media event of interest (e.g., via watermarks, codes,signatures, etc.) and/or access data indicative of a scheduled mediaevent of interest to trigger operation of a mobile device to gather userattention data. For example, one device (e.g., a set meter) triggersoperation of cameras, sensors, and/or other data gathering devices in asecond device (e.g., a mobile device) and causes the second device toreport the gathered data indicative of user attention back to the firstdevice and/or to a remote reporting facility. The user attention data isthen reconciled with media presentation information gathered by thefirst device and/or AME to correct audience measurement data.

Example methods, apparatus, systems, and articles of manufacture formobile device attention detection are disclosed herein. Further examplesand combinations thereof include the following:

Example 1 includes an apparatus comprising a mobile meter to receive,from an external device, a signal to gather user attention data, andtransmit the user attention data, an interval timer to activate a timeperiod for determining attention of a user, and an attention determinerto generate the user attention data during the time period.

Example 2 includes the apparatus of example 1, wherein the attentiondeterminer is to activate a camera on a mobile device and determine if aface is detected by the camera during the time period and based on anorientation of the face.

Example 3 includes the apparatus of example 2, wherein the attentiondeterminer is to generate the user attention data indicative ofattention of the user being on the mobile device based on the face beingdetected by the camera and the orientation of the face being toward themobile device during the time period.

Example 4 includes the apparatus of example 2, wherein the attentiondeterminer is to generate the user data indicative of attention of theuser being away from the mobile device based on one or more of (1) theface not being detected by the camera during the time period, or (2) theface being detected by the camera and the orientation of the face beingaway from the mobile device during the time period.

Example 5 includes the apparatus of example 1, wherein the attentiondeterminer is to determine user interaction with a mobile device duringthe time period, and generate the user attention data based on the userinteraction with the mobile device.

Example 6 includes the apparatus of example 5, wherein the attentiondeterminer is to determine user interaction with the mobile device basedon an application launch on the mobile device.

Example 7 includes the apparatus of example 5, wherein the attentiondeterminer is to determine user interaction with the mobile device basedon user touch on a screen of the mobile device.

Example 8 includes the apparatus of example 5, wherein the attentiondeterminer is to determine user interaction with the mobile device basedon an external device connection to the mobile device.

Example 9 includes the apparatus of example 1, wherein the mobile meteris to receive the signal when a presentation of an advertisement isdetected on a media device within proximity of the mobile meter.

Example 10 includes the apparatus of example 9, wherein the signal isbased on at least one of a watermark or a signature of theadvertisement.

Example 11 includes a method comprising receiving, from an externaldevice, a signal to gather user attention data, activating, by executinginstructions with a processor, a time period for determining attentionof a user, generating, by executing instructions with the processor, theuser attention data during the time period, and transmitting the userattention data.

Example 12 includes the method of example 11, further includingactivating, by executing instructions with the processor, a camera on amobile device, and determining, by executing instructions with theprocessor, if a face is detected by the camera during the time periodand based on an orientation of the face.

Example 13 includes the method of example 12, wherein the generating theuser attention data during the time period includes generating userattention data indicative of the attention of the user being on themobile device based on the face being detected by the camera and theorientation of the face being toward the mobile device during the timeperiod.

Example 14 includes the method of example 12, wherein the generating theuser attention data during the time period includes generating userattention data indicative of the attention of the user being away fromthe mobile device based on one or more of (1) the face not beingdetected by the camera during the time period, or (2) the face beingdetected by the camera and the orientation of the face being away fromthe mobile device during the time period.

Example 15 includes the method of example 11, wherein the generating theuser attention data during the time period includes determining userinteraction with a mobile device during the time period, and generatingthe user attention data based on the user interaction with the mobiledevice.

Example 16 includes the method of example 15, wherein the generating theuser attention during the time period includes determining userinteraction with the mobile device based on an application launch on themobile device.

Example 17 includes the method of example 15, wherein the generating theuser attention during the time period includes determining userinteraction with the mobile device based on user touch on a screen ofthe mobile device.

Example 18 includes the method of example 15, wherein the generating theuser attention during the time period includes determining userinteraction with the mobile device based on an external deviceconnection to the mobile device.

Example 19 includes the method of example 11, wherein receiving, fromthe external device, the signal to gather user attention data is tooccur when a presentation of an advertisement is detected on a mediadevice within proximity of a mobile meter.

Example 20 includes the method of example 19, wherein the signal isbased on at least one of a watermark or a signature of theadvertisement.

Example 21 includes At least one non-transitory computer readable mediumcomprising instructions that, when executed, cause at least oneprocessor to at least receive, from an external device, a signal togather user attention data, activate a time period for determiningattention of a user, generate the user attention data during the timeperiod, and transmit the user attention data.

Example 22 includes the at least one non-transitory computer readablemedium of example 21, wherein the instructions, when executed, cause theat least one processor to activate a camera on a mobile device anddetermine if a face is detected by the camera during the time period andbased on an orientation of the face.

Example 23 includes the at least one non-transitory computer readablemedium of example 22, wherein the instructions, when executed, cause theat least one processor to generate the user attention data as userattention data indicative of attention of the user being on the mobiledevice based on the face being detected by the camera and theorientation of the face being toward the mobile device during the timeperiod.

Example 24 includes the at least one non-transitory computer readablemedium of example 22, wherein the instructions, when executed, cause theat least one processor to generate the user data as user attention dataindicative of attention of the user being away from the mobile devicebased on one or more of (1) the face not being detected by the cameraduring the time period, or (2) the face being detected by the camera andthe orientation of the face being away from the mobile device during thetime period.

Example 25 includes the at least one non-transitory computer readablemedium of example 21, wherein the instructions, when executed, cause theat least one processor to determine user interaction with a mobiledevice during the time period, and generate the user attention based onthe user interaction with the mobile device.

Example 26 includes the at least one non-transitory computer readablemedium of example 25, wherein the instructions, when executed, cause theat least one processor to determine user interaction with the mobiledevice based on an application launch on the mobile device.

Example 27 includes the at least one non-transitory computer readablemedium of example 25, wherein the instructions, when executed, cause theat least one processor to determine user interaction with the mobiledevice based on user touch on a screen of the mobile device.

Example 28 includes the at least one non-transitory computer readablemedium of example 25, wherein the instructions, when executed, cause theat least one processor to determine user interaction with the mobiledevice based on an external device connection to the mobile device.

Example 29 includes the at least one non-transitory computer readablemedium of example 21, wherein receiving, from the external device, thesignal to gather user attention data is to occur when a presentation ofan advertisement is detected on a media device within proximity of amobile meter.

Example 30 includes the at least one non-transitory computer readablemedium of example 29, wherein the signal is based on at least one of awatermark or a signature of the advertisement.

Although certain example methods, apparatus and articles of manufacturehave been disclosed herein, the scope of coverage of this patent is notlimited thereto. On the contrary, this patent covers all methods,apparatus and articles of manufacture fairly falling within the scope ofthe claims of this patent.

The following claims are hereby incorporated into this DetailedDescription by this reference, with each claim standing on its own as aseparate embodiment of the present disclosure.

What is claimed is:
 1. An apparatus comprising: a mobile meter to:receive, from an external device, a signal to gather user attention datawhen a presentation of media is detected on a media device withinproximity of the mobile meter, wherein the user attention data is to beassociated with media presented by the external device; and transmit theuser attention data; an interval timer to, in response to the mobilemeter receiving the signal, activate a time period for determiningattention of a user; and an attention determiner to generate the userattention data during the time period.
 2. The apparatus of claim 1,wherein the attention determiner is to activate a camera on a mobiledevice and determine if a face is detected by the camera during the timeperiod and based on an orientation of the face.
 3. The apparatus ofclaim 2, wherein the attention determiner is to generate the userattention data indicative of attention of the user being on the mobiledevice based on the face being detected by the camera and theorientation of the face being toward the mobile device during the timeperiod.
 4. The apparatus of claim 2, wherein the attention determiner isto generate the user data indicative of attention of the user being awayfrom the mobile device based on one or more of (1) the face not beingdetected by the camera during the time period, or (2) the face beingdetected by the camera and the orientation of the face being away fromthe mobile device during the time period.
 5. The apparatus of claim 1,wherein the attention determiner is to: determine user interaction witha mobile device during the time period; and generate the user attentiondata based on the user interaction with the mobile device.
 6. Theapparatus of claim 5, wherein the attention determiner is to determineuser interaction with the mobile device based on an application launchon the mobile device.
 7. The apparatus of claim 5, wherein the attentiondeterminer is to determine user interaction with the mobile device basedon user touch on a screen of the mobile device.
 8. The apparatus ofclaim 5, wherein the attention determiner is to determine userinteraction with the mobile device based on an external deviceconnection to the mobile device.
 9. The apparatus of claim 1, whereinthe media is an advertisement.
 10. The apparatus of claim 9, wherein thesignal is based on at least one of a watermark or a signature of theadvertisement.
 11. At least one non-transitory computer readable mediumcomprising instructions that, when executed, cause at least oneprocessor to at least: receive, from an external device, a signal togather user attention data when a presentation of media is detected on amedia device within proximity of a mobile meter, wherein the userattention data is to be associated with media presented by the externaldevice; in response to receipt of the signal, activate a time period fordetermining attention of a user; generate the user attention data duringthe time period; and transmit the user attention data.
 12. The at leastone non-transitory computer readable medium of claim 11, wherein theinstructions, when executed, cause the at least one processor toactivate a camera on a mobile device and determine if a face is detectedby the camera during the time period and based on an orientation of theface.
 13. The at least one non-transitory computer readable medium ofclaim 12, wherein the instructions, when executed, cause the at leastone processor to generate the user attention data as user attention dataindicative of attention of the user being on the mobile device based onthe face being detected by the camera and the orientation of the facebeing toward the mobile device during the time period.
 14. The at leastone non-transitory computer readable medium of claim 12, wherein theinstructions, when executed, cause the at least one processor togenerate the user data as user attention data indicative of attention ofthe user being away from the mobile device based on one or more of (1)the face not being detected by the camera during the time period, or (2)the face being detected by the camera and the orientation of the facebeing away from the mobile device during the time period.
 15. The atleast one non-transitory computer readable medium of claim 11, whereinthe instructions, when executed, cause the at least one processor to:determine user interaction with a mobile device during the time period;and generate the user attention data based on the user interaction withthe mobile device.
 16. The at least one non-transitory computer readablemedium of claim 15, wherein the instructions, when executed, cause theat least one processor to determine user interaction with the mobiledevice based on an application launch on the mobile device.
 17. The atleast one non-transitory computer readable medium of claim 15, whereinthe instructions, when executed, cause the at least one processor todetermine user interaction with the mobile device based on user touch ona screen of the mobile device.
 18. The at least one non-transitorycomputer readable medium of claim 15, wherein the instructions, whenexecuted, cause the at least one processor to determine user interactionwith the mobile device based on an external device connection to themobile device.
 19. The at least one non-transitory computer readablemedium of claim 11, wherein the media is an advertisement.
 20. The atleast one non-transitory computer readable medium of claim 19, whereinthe signal is based on at least one of a watermark or a signature of theadvertisement.
 21. A method comprising: receiving, from an externaldevice, a signal to gather user attention data when a presentation ofmedia is detected on a media device within proximity of a mobile meter,wherein the user attention data is to be associated with media presentedby the external device; in response to receipt of the signal,activating, by executing instructions with a processor, a time periodfor determining attention of a user; generating, by executinginstructions with the processor, the user attention data during the timeperiod; and transmitting the user attention data.
 22. The method ofclaim 21, further including: activating, by executing instructions withthe processor, a camera on a mobile device; and determining, byexecuting instructions with the processor, if a face is detected by thecamera during the time period and based on an orientation of the face.23. The method of claim 22, wherein the generating of the user attentiondata during the time period includes generating user attention dataindicative of the attention of the user being on the mobile device basedon the face being detected by the camera and the orientation of the facebeing toward the mobile device during the time period.
 24. The method ofclaim 22, wherein the generating of the user attention data during thetime period includes generating user attention data indicative of theattention of the user being away from the mobile device based on one ormore of (1) the face not being detected by the camera during the timeperiod, or (2) the face being detected by the camera and the orientationof the face being away from the mobile device during the time period.25. The method of claim 21, wherein the generating of the user attentiondata during the time period includes: determining user interaction witha mobile device during the time period; and generating the userattention data based on the user interaction with the mobile device. 26.The method of claim 25, wherein the generating of the user attentiondata during the time period includes determining user interaction withthe mobile device based on an application launch on the mobile device.27. The method of claim 25, wherein the generating of the user attentiondata during the time period includes determining user interaction withthe mobile device based on user touch on a screen of the mobile device.28. The method of claim 25, wherein the generating of the user attentiondata during the time period includes determining user interaction withthe mobile device based on an external device connection to the mobiledevice.
 29. The method of claim 21, wherein the media is anadvertisement.
 30. The method of claim 29, wherein the signal is basedon at least one of a watermark or a signature of the advertisement. 31.An apparatus comprising: means for receiving, from an external device, asignal to gather user attention data when a presentation of media isdetected on a media device within proximity of a mobile meter, whereinthe user attention data is to be associated with media presented by theexternal device; means for starting, in response to receipt of thesignal, a time period for determining attention of a user; means forgenerating the user attention data during the time period; and means fortransmitting the user attention data.
 32. The apparatus of claim 31,further including: means for activating a camera on a mobile device; andmeans for determining if a face is detected by the camera during thetime period and based on an orientation of the face.
 33. The apparatusof claim 32, wherein the means for generating is to generate userattention data indicative of the attention of the user being on themobile device based on the face being detected by the camera and theorientation of the face being toward the mobile device during the timeperiod.